Preparing for IFRS 17

The introduction of new insurance contract standards is causing headaches for insurers around the region as they contend with preparing for the new rules.

One of the biggest challenges comes from IFRS 17’s requirement for insurers to apply discount rates to future cash flow estimates that are “consistent with observable current market prices”. In-house estimates based on historical market averages or subjective assumptions will no longer be acceptable, meaning that insurers will need to “maximise the use of observable inputs”.

Many insurers in the region have expressed fears that meeting such requirements will require costly and significant investment in financial, actuarial and technological resources for companies that are already facing cost pressures.

Indeed, advanced actuarial modelling can be prohibitively expensive when counting the costs of hardware, electricity, cooling, rack space, IT support staff and so on. And the base costs of getting such a system up and running are broadly similar regardless of the size of the company — and can easily add up to millions of dollars.

A more affordable approach that many companies in the region are considering in the run-up to IFRS 17 is to buy software-as-a-service systems from third-party vendors that allow them to run actuarial models in the cloud and can be implemented almost immediately.

“Generating a market-consistent price of the risks that are in our business can be difficult given that insurance liabilities are typically not traded,” says Philip Jackson, a consulting actuary at Milliman in India, during a conference call to insurers about the company’s cloud-based solution for economic scenario generation, known as Chess, that runs on Microsoft’s Azure platform.

Calibration takes the most time, says Clement Bonnet, a consulting actuary with Milliman in Hong Kong. “The whole idea of the calibration process would be to minimise the gap between the output from your model and what you observe in reality,” he says.

This includes choosing an appropriate model for interest rates and equity and real estate indices. “Essentially, all models are wrong, but some are useful,” says Bonnet, quoting statistician George Box.

This is particularly true in Asia, where most insurers are dealing with illiquid financial instruments and limited data.

“That’s definitely one of the key challenges when you calculate an economic scenario table in Asia,” says Bonnet. “An ideal model is as simple as possible. There’s no point using a very complicated model if you don’t have the corresponding assets to calibrate that model.”

While tools such as Chess are user-friendly and make it simple to generate thousands of scenarios, there is no escaping the need for insurers to fully understand how the models are calibrated and what assumptions have been used.

Indeed, despite the availability of such tools, insurers remain concerned about IFRS 17 implementation. A group of insurance bodies, including associations from Korea, Australia and New Zealand, wrote to the International Accounting Standards Board (IASB) in October to warn of “serious operational constraints on insurers’ ability to successfully implement IFRS 17 on the current timelines”.

Just this week, the Philippines deferred by another year the implementation of IFRS 17 for life and non-life insurers to give firms more time to comply. This is in addition to the IASB’s proposed one-year delay to 2022.

“There is a necessity for an additional period of time, in addition to that proposed by the IASB, to prepare for the implementation of IFRS 17,” said Philippines insurance commissioner Dennis Funa.

The tools are available and the costs of implementing them are certainly far lower today than they were in the past, but preparing for IFRS 17 still represents a significant learning curve for many companies in the region.